Risk assessment for the installation and maintenance activities of a low-speed tidal energy converter

The study presented in this paper, is part of the Deep Green project, which includes the development of a power converter/device for employment in low-speed tidal currents. It mainly focuses on the initial steps to investigate the ways on how to minimize the risks during handling, operation and maintenance (O&M) activities of the full-scale device particularly in offshore operations. As a first tep, the full-scale device offshore installation and O&M tasks are considered. The overall risk analysis and decision making methodology is presented including the Hazard Identification (HAZID) approach which is complemented with a risk matrix for various consequence categories including personnel Safety (S), Environmental impact (E), Asset integrity (A) and Operation (O). In this way, all the major risks involved in the mentioned activities are identified and actions to prevent or mitigate them are presented. The results of the HAZID analysis are also demonstrated. Finally, the last section of this paper presents the discussion, conclusions and future actions for the above-mentioned activities regarding the full-scale device

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available datasets of dermatoscopic images. We tackle this problem by releasing the HAM10000 ("Human Against Machine with 10000 training images") dataset. We collected dermatoscopic images from different populations acquired and stored by different modalities. Given this diversity we had to apply different acquisition and cleaning methods and developed semi-automatic workflows utilizing specifically trained neural networks. The final dataset consists of 10015 dermatoscopic images which are released as a training set for academic machine learning purposes and are publicly available through the ISIC archive. This benchmark dataset can be used for machine learning and for comparisons with human experts. Cases include a representative collection of all important diagnostic categories in the realm of pigmented lesions. More than 50% of lesions have been confirmed by pathology, while the ground truth for the rest of the cases was either follow-up, expert consensus, or confirmation by in-vivo confocal microscopy

The Effects of Transport Regulation on the Oil Market: Does Market Power Matter?

Popular instruments to regulate consumption of oil in the transport sector include fuel taxes, biofuel requirements, and fuel efficiency. Their impacts on oil consumption and price vary. One important factor is the market setting. We show that if market power is present in the oil market, the directions of change in consumption and price may contrast those in a competitive market. As a result, the market setting impacts not only the effectiveness of the policy instruments to reduce oil consumption, but also terms of trade and carbon leakage. In particular, we show that under monopoly, reduced oil consumption due to increased fuel efficiency will unambiguously increase the price of oil.transport regulations, oil market, monopoly, terms-of-trade effects, carbon leakage

Green Serves the Dirtiest: On the Interaction between Black and Green Quotas

Tradable black (CO2) and green (renewables) quotas gain in popularity and stringency within climate policies of many OECD countries. The overlapping regulation through both instruments, however, may have important adverse economic implications. Based on stylized theoretical analysis and substantiated with numerical model simulations for the German electricity market, we show that a green quota imposed on top of a black quota does not only induce substantial excess cost but serves the dirtiest power technologies as compared to a black quota regime only.emissions trading, green quotas, overlapping regulation

Simple model frameworks for explaining inefficiency of the clean development mechanism

The Clean Development Mechanism (CDM) is an offset mechanism designed to reduce the overall cost of implementing a given global target for greenhouse gas (GHG) emissions in industrialized"Annex B"countries of the Kyoto Protocol. This paper discusses various ways in which CDM projects do not imply full offset of emissions, thus leading to an overall increase in global GHG emissions when considering the Annex-B emissions increase allowed by the offsets. The authors focus on two ways in which this may occur: baseline manipulation; and leakage. Baseline manipulation may result when agents that carry out CDM projects have incentives to increase their initial (or baseline) emissions in order to optimize the value of CDM credits. Leakage occurs because reductions in emissions under a CDM project may affect market equilibrium in local and/or global energy and product markets, and thereby increase emissions elsewhere. Remedies against these problems are discussed. Such remedies are more obvious for the baseline problem (where one is simply to choose an exogenous baseline independent of the project) than for the leakage problem (which is difficult to prevent, and where a prediction of the effect must rely on information about overall market equilibrium effects).Energy Production and Transportation,Environmental Economics&Policies,Environment and Energy Efficiency,Energy and Environment,Transport Economics Policy&Planning

Energy avalanches in a rice-pile model

We investigate a one-dimensional rice-pile model. We show that the distribution of dissipated potential energy decays as a power law with an exponent $\alpha=1.53$. The system thus provides a one-dimensional example of self-organized criticality. Different driving conditions are examined in order to allow for comparison with experiments.Comment: 8 pages, elsart sty files (provided

An application of LANDSAT multispectral imagery for the classification of hydrobiological systems, Shark River Slough, Everglades National Park, Florida

Multivariant hydrologic parameters over the Shark River Slough were investigated. Ground truth was established utilizing U-2 infrared photography and comprehensive field data to define a control network which represented all hydrobiological systems in the slough. These data were then applied to LANDSAT imagery utilizing an interactive multispectral processor which generated hydrographic maps through classification of the slough and defined the multispectral surface radiance characteristics of the wetlands areas in the park. The spectral response of each hydrobiological zone was determined and plotted to formulate multispectral relationships between the emittent energy from the slough in order to determine the best possible multispectral wavelength combinations to enhance classification results. The extent of each hydrobiological zone in slough was determined and flow vectors for water movement throughout the slough established

Catalytic upgrading of hydrothermal liquefaction biocrudes: Different challenges for different feedstocks

Hydrothermal liquefaction (HTL) followed by catalytic hydrotreating of the produced biocrude is increasingly gaining ground as an effective technology for the conversion of biomass into liquid biofuels. A strong advantage of HTL resides in its great flexibility towards the feedstock, since it is able to treat a large number of different organic substrates, ranging from dry to wet residual biomass. Nevertheless, the characteristics of biocrudes from different typologies of organic materials result in different challenges to be met during the hydrotreating step, leading to differences in heteroatoms removal and in the typology and composition of the targeted products. In this work, biocrudes were catalytically hydrotreated with a commercial NiMo/Al2O3 catalyst at different temperatures and pressures. Sewage sludge biocrude was found to be very promising for the production of straight-chain hydrocarbons in the diesel range, with considerable heteroatoms removal even at mild hydrotreating conditions. Similar results were shown by algal biocrude, although complete denitrogenation is challenging. Upgraded biocrudes from lignocellulosic feedstock (miscanthus) showed high yields in the gasoline range, with a remarkable content of aromatics. Operating at a higher H2 pressure was found to be crucial to prevent coking and decarboxylation reactions.Comment: Accepted manuscript for publication in Renewable Energ

Optimal Timing of Environmental Policy; Interaction Between Environmental Taxes and Innovation Externalities

This paper addresses the impact of endogenous technology through research and development (R&D) and learning by doing (LbD) on the timing of environmental policy. We develop two models, the first with R&D and the second with LbD. We study the interaction between environmental taxes and innovation externalities in a dynamic economy and prove policy equivalence between the second-best R&D and the LbD model. Our analysis shows that the difference found in the literature between optimal environmental policy in R&D and LbD models can partly be traced back to the set of policy instruments available, rather than being directly linked to the source of technological innovation. Arguments for early action in LbD models carry over to a second-best R&D setting. We show that environmental taxes should be high compared to the Pigouvian levels when an abatement industry is developing. We illustrate our analysis through numerical simulations on climate change policy.Environmental Policy, Technological Change, Research and Development, Learning by Doing